from datasets import GeneratorBasedBuilder, DatasetInfo, SplitGenerator, Split, Features, Value, Audio,SplitGenerator, Split import os import json import csv import datasets from datasets.utils.py_utils import size_str from tqdm import tqdm _BASE_URL = "https://huggingface.co/datasets/iulik-pisik/audio_vreme/resolve/main/" _AUDIO_URL = _BASE_URL + "audio/{split}.tar" _TRANSCRIPT_URL = _BASE_URL + "transcript/{split}.tsv" class AudioVreme(GeneratorBasedBuilder): def _info(self): return DatasetInfo( description="Dataset de vreme preluat de la ProTV", features=Features({ "path": Value("string"), "audio": Audio(sampling_rate=16000), "sentence": Value("string"), "gender": Value("string"), "name": Value("string"), }), supervised_keys=("audio", "transcript"), homepage="https://huggingface.co/datasets/iulik-pisik/audio_vreme", citation="Referința de citare a datasetului", ) def _split_generators(self, dl_manager): audio_urls = { "train_audio": _AUDIO_URL.format(split="train"), "test_audio": _AUDIO_URL.format(split="test"), "validation_audio": _AUDIO_URL.format(split="validation"), } tsv_urls = { "train_tsv": _TRANSCRIPT_URL.format(split="train"), "test_tsv": _TRANSCRIPT_URL.format(split="test"), "validation_tsv": _TRANSCRIPT_URL.format(split="validation"), } downloaded_audio_files = dl_manager.download_and_extract(audio_urls) downloaded_tsv_files = dl_manager.download(tsv_urls) return [ SplitGenerator( name=Split.TRAIN, gen_kwargs={ "archive_path": downloaded_audio_files["train_audio"], "tsv_path": downloaded_tsv_files["train_tsv"], }, ), SplitGenerator( name=Split.TEST, gen_kwargs={ "archive_path": downloaded_audio_files["test_audio"], "tsv_path": downloaded_tsv_files["test_tsv"], }, ), SplitGenerator( name=Split.VALIDATION, gen_kwargs={ "archive_path": downloaded_audio_files["validation_audio"], "tsv_path": downloaded_tsv_files["validation_tsv"], }, ), ] def _generate_examples(self, archive_path, tsv_path): with open(tsv_path, encoding="utf-8") as f: reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE) for row in tqdm(reader, desc="Se citesc datele..."): audio_file_name = row["path"] audio_path = os.path.join(archive_path, audio_file_name) if not os.path.isfile(audio_path): continue yield audio_file_name, { "path": audio_path, "audio": audio_path, "sentence": row["sentence"], "gender": row["gender"], "name": row["name"] }